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AI-Augmented Software Engineering may sound like a mouthful, but it’s actually fairly straightforward. AI-Augmented Software Engineering is the integration of AI and ML, Artificial Intelligence and Machine Learning for software development - augmenting the engineering. #AIsoftware #AIEngineering #DevOps #aiinnovation #Business #technology #softwareengineering #aidevelopment

The business value is enormous and this is a leading area of early AI adoption.

When done right, developers can create better applications more quickly than without the AI augmentation.

Let’s dig into AI-Augmented Software Engineering.

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AI-Augmented Software Engineering can aid software engineers with code generation, code completion, bug detection, testing and more… which increases developer productivity and accelerates the time to market with new applications.

But make no mistake, this is an emerging technology that doesn’t have everyone convinced, and it currently sits atop the Gartner Hype Cycle.

Recently, GitLab CISO Josh Lemos commented at Info-Tech LIVE that Code generation and code augmentation equate to about 30% of a typical developer’s time. With the rest ate up in planning, designing, paying down other tech debt and other work other than writing code.

At GitLab, they seek to accelerate every part of the software development lifecycle… which removes some of the other work, so they can spend more time developing software.

Now, that’s business value… but is it a trap?

Data quality issues aside, we all know AI struggles with accuracy and hallucinations persist. That will iron itself out over time, but what if the new code written by bots is worse that some of the code coders have already had to clean up from poorly performing humans over the years?

What if we can’t resolve the potential issues that AI-Augmented Software Engineering can create?

Enterprise organizations, are called that in part, because they take risks.

Only time will tell how patient the outperforming enterprise should be here, but it sure sounds like fertile ground for huge business value.

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Splunk highlights AI-Augmented Software Engineering as providing benefits to the IT Industry.
They say “the traditional method of relying solely on human coders throughout the entire development lifecycle is gradually becoming obsolete. 

Instead, AI-augmented software engineering has come into the arena to make the software engineering process faster, easier, and more reliable.” 

For instance, AI developers leverage AI tools to: 
Generate code
Fix bugs, and
Create documentation.

Splunk highlights how In  AI-augmented software engineering, developers can simply copy and paste the existing code and ask AI tools to identify bugs and performance issues in the code snippets. The AI tool will then automatically…
Analyze the code using existing execution traces, errors, issue reports, etc.
Identify the root cause, and
Provide suggestions on improving the code. 

They tout others, too.

Gartner boasts five was AI Augmented Software Engineering can provide business value.

A couple of them are One, to deploy generative AI as an app modernization tool - providing a quick and easy automated way to transform and modernize software code.

And two, use generative AI to explain, detect and measure technical debt and its impact. you can look up the others.

What is your experience or perspective? We’d love to see it in the comments below.

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We’re here for business and technical leaders of large enterprise organizations, and we have deep experience.

And hey, hope to see you on the other side.

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00:10 What is AI-Augmented Software Engineering

00:54 Code generation, Code completion, Bug detection

01:11 GitLab CISO Josh Lemos Talked at Info-Tech LIVE

01:56 What if The New Code Written by Bots is Worse

03:35 AI Augmented Software Engineering can Provide Business Value.